# Identifying individual-specific gait signatures for stroke rehabilitation > **NIH NIH F31** · EMORY UNIVERSITY · 2023 · $47,694 ## Abstract PROJECT SUMMARY/ABSTRACT Stroke gait deficits are complex and marked by adverse effects on kinematics, kinetics, gait symmetry, and inter- and intra- limb joint coordination across different phases of the gait cycle. One intervention simply cannot target the high inter-individual variability of deficits observed in post-stroke gait. Approximately 2/3 of stroke survivors have persistent gait impairments despite being discharged from rehabilitation, and one reason could be the lack of tailored rehabilitation approaches to address their individual-specific impairments. The development of tailored rehabilitation approaches, however, is limited by the lack of robust metrics to identify and analyze individual- specific differences in gait. The objective of this work is to develop a sensitive, data-driven, consistent characterization of gait using continuous, multi-joint gait dynamics. The dynamics of gait will be extracted from measured kinematics (joint angles) and used to develop individual-specific gait characterizations, which we coined the ‘gait signature.’ We will use these gait signatures to probe the mechanisms underlying stroke gait impairment using rehabilitation techniques, specifically Fast functional electrical stimulation (FastFES). FastFES is a gait rehabilitation intervention that targets ankle dorsiflexor muscles to address foot drop, and ankle plantarflexor muscles to improve ankle torque at push-off. The literature suggests that response to FastFES depends on the precise alignment between a specific muscle coordination deficit and the gait rehabilitation modality. This suggests that knowledge of an individual’s specific gait impairment before rehabilitation can predict their response to therapy. Since FastFES is known to target ankle deficits related to ankle push-off, I will probe this theory and evaluate whether gait signatures can encode ankle push-off corrections in response to a single session exposure to FastFES. I predict that stroke individuals with ankle-related push-off deficits will show the greatest response or change in their gait signature towards normative (able-bodied) gait. Preliminary findings show that gait signatures accurately discriminate between different stroke individuals. A noteworthy finding is that our gait signatures do not appear to cluster according to walking speed, leading to our hypothesis that gait signatures distinguish individual-specific differences in stroke gait corresponding to what we know about heterogeneity in stroke gait impairments. We aim to determine the functional biomechanical relevance of various clusters of gait signatures, and we will determine whether FastFES targets a specific cluster of individuals depending on the biomechanical features, characteristics, or deficits that they have. Furthermore, we will determine whether gait signatures before FastFES exposure can predict whether stroke-survivor will be a potential responder to FastFES. If successful, gait signatures will prove ... ## Key facts - **NIH application ID:** 10605158 - **Project number:** 5F31HD107968-02 - **Recipient organization:** EMORY UNIVERSITY - **Principal Investigator:** Taniel Solarnge Winner - **Activity code:** F31 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $47,694 - **Award type:** 5 - **Project period:** 2022-06-01 → 2025-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10605158 ## Citation > US National Institutes of Health, RePORTER application 10605158, Identifying individual-specific gait signatures for stroke rehabilitation (5F31HD107968-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10605158. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*